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. 2025 May 16;151(5):168.
doi: 10.1007/s00432-025-06219-5.

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer

Alex Besson  1   2 , Ke Cao  1 , Ahmed Mardinli  1 , Lara Wirth  1 , Josephine Yeung  1 , Rory Kokelaar  1   3 , Peter Gibbs  4   5 , Fiona Reid  1   3 , Justin M Yeung  6   7
Affiliations

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer

Alex Besson et al. J Cancer Res Clin Oncol. .

Abstract

Purpose: Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokinetic and pharmacodynamic profile of cytotoxic agents and could inform optimal dosing. This study aims to assess how lumbosacral body composition influences adverse events in patients receiving neoadjuvant chemotherapy for rectal cancer.

Methods: A retrospective study (February 2013 to March 2023) examined the impact of body composition on neoadjuvant treatment outcomes for rectal cancer patients. Staging CT scans were analysed using a validated AI model to measure lumbosacral skeletal muscle (SM), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue volume and density. Multivariate analyses explored the relationship between body composition and chemotherapy outcomes.

Results: 242 patients were included (164 males, 78 Females), median age 63.4 years. Chemotherapy dose reductions occurred more frequently in females (26.9% vs. 15.9%, p = 0.042) and in females with greater VAT density (-82.7 vs. -89.1, p = 0.007) and SM: IMAT + VAT volume ratio (1.99 vs. 1.36, p = 0.042). BSA was a poor predictor of dose reduction (AUC 0.397, sensitivity 38%, specificity 60%) for female patients, whereas the SM: IMAT + VAT volume ratio (AUC 0.651, sensitivity 76%, specificity 61%) and VAT density (AUC 0.699, sensitivity 57%, specificity 74%) showed greater predictive ability. Body composition didn't influence dose adjustment of male patients.

Conclusion: Lumbosacral body composition outperformed BSA in predicting adverse events in female patients with rectal cancer undergoing neoadjuvant chemotherapy.

Keywords: Artificial intelligence; Body composition; Chemotherapy; Dose modification; Rectal cancer.

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Conflict of interest statement

Declarations. Disclosure: The authorship have no disclosures to declare. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
SM: IMAT + VAT volume prediction of dose modification for female patients
Fig. 2
Fig. 2
Female chemotherapy dose adjustment ROC Curve: BSA compared to VAT density & SM: IMAT + VAT volume
See this image and copyright information in PMC

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